Managing prices has always been an activity of keen interest to businesses, but it has become even more critical to do it well. Over the past decade many companies have found their ability to raise prices has been constrained by intense competition resulting from Internet commerce, global competition and other factors. One tool for dealing with this pressure is price and revenue optimization (PRO), an analytic methodology that calculates how demand varies at different price levels and then uses that algorithm to recommend prices that should optimally balance revenue and profit objectives. Computer-supported PRO began in earnest in the 1980s as the airline and hospitality industries adopted revenue management practices in efforts to maximize returns from less flexible travelers (such as people on business trips) while minimizing the unsold inventory by selling incremental seats on flights or nights in hotel rooms at discounted prices to more discretionary buyers (typically vacationers). Price and revenue optimization algorithms are designed to enable a company to achieve fatter profit margins than are possible with a monolithic pricing strategy. Using PRO, airlines and hotels catering mainly to less price-sensitive business travelers found they could match discounters’ fares and rates to fill available seats and rooms without having to forgo profits from their high-margin customers.

PRO has expanded into other industries as computing power and data storage become ever less expensive, as software vendors have improved their techniques and algorithms to deliver better results and as the software has grown increasingly user-friendly. While the concepts underlying all PRO software are the same, there are different categories in which it is customized to meet the needs of specific industries. Retailers in particular have requirements that are best met by using applications that manage markdowns.

At the heart of price and revenue optimization is the concept of demand-based pricing. As its name suggests, demand-based pricing is a method that sets a price that is controlled by the seller’s assessment of what the buyer is willing to pay, which in turn is based on an estimate of a good’s or a service’s perceived value to the buyer. Companies use demand-based pricing to optimize – rather than simply maximize – their pricing to achieve revenue and profitability objectives. It uses data to estimate where the prospective buyer sits on a demand curve and therefore how much the individual is likely to pay. In some respects this is similar to what happens daily in souks, bazaars and other markets in cultures that do not insist on set prices. However, software makes demand-based pricing practical in large businesses and facilitates its introduction in societies used to set pricing.

Advanced analytic applications – especially for price and revenue optimization – have been gaining ground in corporate management because they have demonstrated to work. Significantly, they have the ability to deliver results that are unobtainable otherwise. Such software can crunch through very large data sets rapidly, apply purpose-built algorithms and automate the repetitive mechanical steps needed to put decisions into action. It also ensures consistency and supports objectivity in how executives and managers make decisions. Price and revenue optimization applications have benefited as the cost and complexity of the computing resources needed to use them have declined.

The adoption of PRO software is part of a broader trend of using applications to support fact-based decisions that once depended on experience and hunches. However, our benchmark research on the Office of Finance finds that just 20 percent of companies use price optimization analytics extensively. Only one-third look at product profitability. We think that more of them should do both. Analytic applications can digest a considerable amount of data to segment markets into useful groupings, pinpoint correlations and divine trends, to name a few tasks necessary for pricing management. However, companies investigating PRO software should narrow their search to applications that are appropriate for their specific business. While some offerings have broader applicability than others, no software product now available performs well in every industry.

Retail businesses that have multiple outlets, especially those that deal in trend- or fashion-driven products, face unique price and revenue optimization challenges and this affects the design of pricing management applications aimed at retailers. Many of these businesses are self-service, exclusively so if they are Internet-based, so there is no face-to-face contact during the product selection process. Negotiating prices isn’t feasible in most multiple-outlet retail settings in developed economies because of cultural norms and the hazard of delegating these decisions to front-line staff in even a midsize company. Unlike business-to-business transactions that involve ongoing relationships with established products, most stores today know little about most of their customers, so there is no direct way of judging an individual’s price sensitivity for the specific purchase at hand. In other words, most of the elements that support PRO strategies in analytics used for other types of businesses aren’t available to multiple-outlet retailers.

Since they usually cannot gauge the price sensitivity of their customers, retailers take a different approach: Let the merchandise do the talking. Products that aren’t selling well are by definition overpriced in that market. Retailers have used markdowns as a crude tool of price optimization for a long time. Offering a 30 percent discount near the end of the season is usually better than having to take a 60 percent haircut from a close-out specialist. Yet deciding when and by how much to reduce prices and then implementing the reductions at the store level in an optimal fashion is complicated because of the number of variables that must be considered. There are different types of merchandise, including long-life categories of goods that can be offered for sale for years, short-life fashion and fad items that are offered only once and those somewhere in between. There are differences in demand patterns and price sensitivity between regions and even at the store level. Seasonality, weather and movable holidays such as Easter and Thanksgiving must be considered.

Using analytic applications is superior to relying on experience and intuition because applications often demonstrate that the best decisions go against the grain of established practices. For example, retailers have found that smaller markdowns applied earlier and more frequently produce better results (that is, greater volumes sold at a lower aggregate markdown) than the common practice of making one or two big moves. Until the data became available, minimizing the number of markdowns was reasonable because of the cost in staff time to change prices at the store level. However, retailers using smaller and more frequent markdowns more than pay for these costs and then establish processes to facilitate price changes. Some retailers have found to their surprise that early small markdowns reduce the overall cost of markdowns. Analytic applications also are able to deal with a range of variables that retailers can use in markdown management. For example, they can vary percentages and frequency by size and color as well as by location. The software can monitor sales and inventory levels by the SKU at each store and automatically make detailed recommendations on how to adjust pricing. The software also enables retailers with multichannel operations (usually an online presence) to manage pricing decisions optimally across different types of outlets.

PRO software designed for markdown management also enhances the ability of a multiple-outlet retailers to run their business in a way that maximizes the productivity of their stores measured in sales or gross margin per square foot (or meter) or per linear foot (or meter) of shelf space. Items taking up space in a store or on a shelf have an opportunity cost in that they could be replaced by faster-moving or more profitable goods. Modeling the cost of the uplift required to free up space can result in a more attractive mix of merchandise that will improve returns.

While usability and capability of markdown management software have been improving, retailers face internal challenges in being able to utilize it. Analytic applications are only as good as the data available to feed the systems. Our research consistently finds that data accuracy and availability are significant challenges that almost all midsize and large companies face. Using markdown management software successfully also involves a change management effort requiring heavy involvement by senior management to endorse changes in how the organization handles day-to-day business as well as changes to processes and training and considerable amounts of follow-up to ensure compliance with the new ways of doing business.

Information technology is playing an increasingly important role in how companies conduct their businesses. Analytic applications can transform how entire industries operate. Today, airline and hospitality businesses operate very differently from how they ran in the 1980s because of the Internet and analytics. All sorts of businesses are finding that price and revenue optimization software enables them to improve their results measurably. Retailers should look into markdown management software as a way to fatten their bottom line. Other types of businesses also should consider PRO tools as applied to their particular needs.

SYSPRO is a 35-year-old ERP vendor that focuses on products for midsize companies, particularly those in manufacturing and distribution. In manufacturing, SYSPRO supports make, configure and assemble, engineer to order, make to stock and job shop environments. The company attempts to differentiate itself through vertical specialization and its years of ongoing development, which can reduce the need for customization and cut the cost of initial and ongoing configuration to suit the needs of companies in these industries, thereby cutting the total cost of ownership. Worldwide its targeted verticals include electronics, food, machinery and equipment and medical devices; in the United States, it adds automotive parts (original equipment and after-market) and energy.

Continuing to expand its product portfolio, SYSPRO recently introduced new modules for voyage and container tracking that should be of interest to manufacturing or distribution companies that import goods or parts. These are designed to be the missing link in supply chain management (SCM), connecting the flow of data from purchase order to physical receipt of the goods at a factory, warehouse or distribution center. Integrating voyage and container tracking into its ERP system enables such a company to have a centralized view of the full supply chain, providing fuller and more consistent visibility into the status of inventories from the point of their acquisition and therefore an easier and more effective means of supply chain and sales and operations planning (S&OP). Such a system could replace the sets of disconnected spreadsheets stored on individual computers in many companies, and the time is right to do that. Today’s longer supply chains introduce greater risk and uncertainty in SCM and S&OP. SYSPRO’s new modules can help companies with long supply chains mitigate this risk and provide greater agility to respond to changes in the status of inventories as they occur in transit. Bringing together this information with the full range of data captured in its ERP system also should give companies a better understanding of their performance. This is consistent with our benchmark research on operational business intelligence, which finds managing performance and risk and identifying improvement opportunities among the top five reasons for using operational intelligence. SYSPRO’s initial release of the two modules supplies the basics needed to assign purchase orders to specific containers, assign customer orders to the inventory in the containers and assign containers to specific vessels. The product roadmap calls for substantial enhancements in built-in analytics and physical tracking (knowing the location of specific containers)that buyers will find useful.

Tracking the location and projecting the expected arrival of products, parts and supplies from the physical receipt of those goods enables a company to manage its supply chain more intelligently. That is, knowing exactly what inventory is in which containers, which containers are on which ship and when individual ships are expected to arrive provides the ability to plan and allocate inventory further back in the supply chain with greater certainty. It makes supply chain planning and management as well as an S&OP process more effective with much less effort since the information about the inventory is timely, reliable, consistent and integrated with the full ERP system and kept in a central data repository. Reliable data about inventory in transit is available immediately and updates about departure and expected arrival information can provide earlier visibility into supply and scheduling issues. Users also have the ability to allocate individual goods or parts to specific customers, distribution or production locations from the point at which the inventory is loaded into the container. As conditions change, companies can update these allocations. While it happens rarely, containers sometimes are lost at sea (approximately 10,000 annually – about 0.1% of those in use) or destroyed during loading or unloading. Shipping schedules are inexact, and there can be delays caused by strikes, quarantines or official inspections that are difficult or impossible to predict with any certainty. These are ample reasons to invest in software that enables more flexible planning and reaction.

Integrating data about inventory along an extended supply chain also can provide managers and executives with a more robust set of analytics that are available on a more timely basis with far less effort than what’s required when the data is stored and managed in desktop spreadsheets. Companies are better able to track suppliers (freight forwarders and shippers), measure and track the accuracy of the container manifests (actual items vs. bills of lading) and keep tabs on these over time to rate supplier reliability or isolate seasonal or other factors and make more intelligent more choices and potentially more accurate plans. Companies also can assign voyage- or container-specific charges to individual inventory items to better understand to total, as-delivered cost of items.

All of the information that SYSPRO’s ERP system collects is available on mobile devices using its Espresso platform. In our research on business technology innovation companies listed mobility as their third-most important technology innovation priority; it enables anytime, anywhere access to data, reports, dashboards and analytics. Especially for those who aren’t working at a desk in an office (such as sales people tracking orders or manufacturing or supply chain managers), access to this information on a mobile device can improve performance by providing more timely alerts and the ability to collaborate more intelligently to advance a process.

To SYSPRO customers that regularly use container shipping I recommend evaluating how the voyage and container modules might allow them to manage these supply chains and their sales and operations planning more effectively, while reducing the time they may be spending using desktop spreadsheets to manage these elements of their business. I also recommend that midsize companies (or midsize divisions of larger companies) in SYSPRO’s target verticals that are considering purchase of an ERP system and that need to manage long supply chains that utilize container shipping should put SYSPRO on their list of vendors to evaluate. Be aware that because the new modules are designed to be part of an integrated ERP system, they are impractical for purchase as stand-alone software or integrated into another vendor’s ERP system.